Real-Time Data Streaming in the Insurance Industry

Insurance companies are facing similar challenges like all other disrupted market segments like the change of customer expectations and hence the need of differentiating itself new as a brand in a challenging market environment. But at the same time, it underlies a very strict regulatory pressure.

Generali Switzerland, as many market leaders in every industry, have understood the power of data to reimagine their markets, customers, products, and business model and managed this change by building their Connection Platform within one year.

Christian Nicoll, Director of Platform Engineering & Operations at Generali Switzerland guides us through their journey of setting up an event-driven architecture to support their digital transformation project.

Attend this online talk and learn more about:
-How Generali managed it to assemble various parts to one platform
-The architecture of the Generali Connection Platform, including Confluent, Kafka, and Attunity.
-Their challenges, best practices, and lessons learned
-Generali’s plans of expanding and scaling the Connection Platform
-Additional Use Cases in regulated markets like retail banking

When it comes to the fast-paced nature of capital markets and IoT, the ability to analyze data in real time is critical to gaining an edge. It’s not just about the quantity of data you can analyze at once, it’s about the speed, scale, and quality of the data you have at your fingertips.

Modern streaming data technologies like Apache Kafka and the broader Confluent platform can help detect opportunities and threats in real time. They can improve profitability, yield, and performance. Combining Kafka with Panopticon visual analytics provides a powerful foundation for optimizing your operations.

This online talk will include in depth practical demonstrations of how Confluent and Panopticon together support several key applications. You will learn:

-Why Apache Kafka is widely used to improve performance of complex operational systems
-How Confluent and Panopticon open new opportunities to analyze operational data in real time
-How to quickly identify and react immediately to fast-emerging trends, clusters, and anomalies
-How to scale data ingestion and data processing
-Build new analytics dashboards in minutes

Most companies start their cloud journey with a new use case, or a new application. Sometimes these applications can run independently in the cloud, but often times they need data from the on premises datacenter. Existing applications will slowly migrate, but will need a strategy and the technology to enable a multi-year migration.

In this session, we will share how companies around the world are using Confluent Cloud, a fully managed Apache Kafka® service, to migrate to Google Cloud Platform. By implementing a central-pipeline architecture using Apache Kafka to sync on-prem and cloud deployments, companies can accelerate migration times and reduce costs.

Register now to learn:
-How to take the first step in migrating to GCP
-How to reliably sync your on premises applications using a persistent bridge to cloud
-How Confluent Cloud can make this daunting task simple, reliable and performant

When it comes to the fast-paced nature of capital markets and IoT, the ability to analyze data in real time is critical to gaining an edge. It’s not just about the quantity of data you can analyze at once, it’s about the speed, scale, and quality of the data you have at your fingertips.

Modern streaming data technologies like Apache Kafka and the broader Confluent platform can help detect opportunities and threats in real time. They can improve profitability, yield, and performance. Combining Kafka with Panopticon visual analytics provides a powerful foundation for optimizing your operations.

This online talk will include in depth practical demonstrations of how Confluent and Panopticon together support several key applications. You will learn:

-Why Apache Kafka is widely used to improve performance of complex operational systems
-How Confluent and Panopticon open new opportunities to analyze operational data in real time
-How to quickly identify and react immediately to fast-emerging trends, clusters, and anomalies
-How to scale data ingestion and data processing
-Build new analytics dashboards in minutes

Insurance companies are facing similar challenges like all other disrupted market segments like the change of customer expectations and hence the need of differentiating itself new as a brand in a challenging market environment. But at the same time, it underlies a very strict regulatory pressure.

Generali Switzerland, as many market leaders in every industry, have understood the power of data to reimagine their markets, customers, products, and business model and managed this change by building their Connection Platform within one year.

Christian Nicoll, Director of Platform Engineering & Operations at Generali Switzerland guides us through their journey of setting up an event-driven architecture to support their digital transformation project.

Attend this online talk and learn more about:
-How Generali managed it to assemble various parts to one platform
-The architecture of the Generali Connection Platform, including Confluent, Kafka, and Attunity.
-Their challenges, best practices, and lessons learned
-Generali’s plans of expanding and scaling the Connection Platform
-Additional Use Cases in regulated markets like retail banking

Digital transformation is more than just a buzzword, it’s become a necessity in order to compete in the modern era. At the heart of digital transformation is real-time data. Your organization must respond in real time to every customer experience transaction, sale, and market movement in order to stay competitive.

Streaming data technologies like Apache Kafka® and Confluent KSQL, the streaming SQL engine for Apache Kafka, are being used to detect and react to events as they occur. Combining this technology with the analytics insights from RCG and visualizations from Arcadia Data delivers a powerful foundation for driving real time business decisions. Use cases span across industries and include retail transaction cost analysis, automotive maintenance and loyalty program management, and credit card fraud detection.

Join experts from Confluent, RCG and Arcadia Data for a discussion and demo on how companies are integrating streaming data technologies to transform their business.

Watch now to learn:

-Why Apache Kafka is widely used for real-time event monitoring and decisioning
-How to integrate real-time analytics and visualizations to drive business processes
-How KSQL, streaming SQL for Kafka, can easily transform and filter streams of data in real time

Detecting fraudulent activity in real time can save a business significant amounts of money, but has traditionally been an area requiring a lot of complex programming and frameworks, particularly at scale. Using KSQL, it's possible to use just SQL to build scalable real-time applications.

In this talk, we'll look at:
-What KSQL is, and how its ability to join streams of events can be used to detect possibly fraudulent activity based on a stream of ATM transactions.
-How easy it is to integrate Kafka with other systems—both upstream and downstream—using Kafka Connect to stream from a database into Kafka, and from Kafka into Elasticsearch.

Analytic pipelines running purely on batch processing systems can suffer from hours of data lag, resulting in accuracy issues with analysis and overall decision-making. Join us for a demo to learn how easy it is to integrate your Apache Kafka® streams in Apache Druid (incubating) to provide real-time insights into the data.

-The benefits of combining a real-time streaming platform with a comprehensive analytics stack
-Building an analytics pipeline by integrating Confluent Platform and Imply
-How KSQL, streaming SQL for Kafka, can easily transform and filter streams of data in real time
-Querying and visualizing streaming data in Imply
-Practical ways to implement Confluent Platform and Imply to address common use cases such as analyzing network flows, collecting and monitoring IoT data and visualizing clickstream data

Confluent Platform, developed by the creators of Kafka, enables the ingest and processing of massive amounts of real-time event data. Imply, the complete analytics stack built on Druid, can ingest, store, query and visualize streaming data from Confluent Platform, enabling end-to-end real-time analytics. Together, Confluent and Imply can provide low latency data delivery, data transform, and data querying capabilities to power a range of use cases.

Many enterprises faced with silo’ed, batch-oriented, legacy systems struggle to compete in this new digital-first world. Adhering to the ‘If it’s not broken don’t fix it’ mentality leaves the door wide open for native digital challengers to grow and succeed. To stay competitive, your organization must respond in real time to every customer experience transaction, sale, and market movement. But how do you get there? First, you must change your mindset.

As streaming platforms become central to data strategies, companies both small and large are re-thinking their enterprise architecture with real-time context at the forefront. Monoliths are evolving into microservices. Datacenters are moving to the cloud. What was once a ‘batch’ mindset is quickly being replaced with stream processing as the demands of the business impose real-time requirements on technology leaders.

Join Argyle, in partnership with Confluent, in our 2018 CIO Virtual Event: The Digital Transformation Mindset – More Than Just Technology. During the webinar we’ll learn how leading companies across industries rely on a streaming platform to make event-driven architectures central to:

• How data strategies and IT initiatives are improving the digital customer experiences
• How executives are reducing risk with real time monitoring and anomaly detection
• Increasing operational agility with microservices and IoT architectures within organizations

Insurance companies are facing similar challenges like all other disrupted market segments like the change of customer expectations and hence the need of differentiating itself new as a brand in a challenging market environment. But at the same time, it underlies a very strict regulatory pressure.

Generali Switzerland, as many market leaders in every industry, have understood the power of data to reimagine their markets, customers, products, and business model and managed this change by building their Connection Platform within one year.

Christian Nicoll, Director of Platform Engineering & Operations at Generali Switzerland guides us through their journey of setting up an event-driven architecture to support their digital transformation project.

Attend this online talk and learn more about:
-How Generali managed it to assemble various parts to one platform
-The architecture of the Generali Connection Platform, including Confluent, Kafka, and Attunity.
-Their challenges, best practices, and lessons learned
-Generali’s plans of expanding and scaling the Connection Platform
-Additional Use Cases in regulated markets like retail banking

Most companies start their cloud journey with a new use case, or a new application. Sometimes these applications can run independently in the cloud, but often times they need data from the on premises datacenter. Existing applications will slowly migrate, but will need a strategy and the technology to enable a multi-year migration.

In this session, we will share how companies around the world are using Confluent Cloud, a fully managed Apache Kafka service, to migrate to AWS. By implementing a central-pipeline architecture using Apache Kafka to sync on-prem and cloud deployments, companies can accelerate migration times and reduce costs.

In this online talk we will cover:
•How to take the first step in migrating to AWS
•How to reliably sync your on premises applications using a persistent bridge to cloud
•Learn how Confluent Cloud can make this daunting task simple, reliable and performant
•See a demo of the hybrid-cloud and multi-region deployment of Apache Kafka

In 2010, LinkedIn began developing Apache Kafka®. In 2011, Kafka was released an Apache open source project. Since then, the use of Kafka has grown rapidly in a variety of businesses. Now more than 30% of Fortune 500 companies are already using Kafka.

In this 60-minute online talk, Confluent Co-founder Jun Rao will:
-Explain how Kafka became the predominant publish/subscribe messaging system that it is today
-Introduce Kafka's most recent additions to its set of enterprise-level features
-Demonstrate how to evolve your Kafka implementation into a complete real-time streaming data platform that functions as the central nervous system for your organization

With the evolution of data-driven strategies, event-based business models are influential in innovative organizations. These new business models are built around the availability of real-time information on customers, payments and supply chains. As businesses look to expand traditional revenues, sourcing events from enterprise applications, mobile apps, IoT devices and social media in real time becomes essential to staying ahead of the competition.

Join John Santaferraro, Research Director at leading IT analyst firm Enterprise Management Associates (EMA), and Lyndon Hedderly, Director of Customer Solutions at Confluent, to learn how business and technology leaders are adopting streaming strategies and how the world of streaming data implementations have changed for the better.

You will also learn how organizations are:
-Adopting streaming as a strategic decision
-Using streaming data for a competitive advantage
-Using real-time processing for their applications
-Evolving roadblocks for streaming data
-Creating business value with a streaming platform

Most companies start their cloud journey with a new use case, or a new application. Sometimes these applications can run independently in the cloud, but often times they need data from the on premises datacenter. Existing applications will slowly migrate, but will need a strategy and the technology to enable a multi-year migration.

In this session, we will share how companies around the world are using Confluent Cloud, a fully managed Apache Kafka service, to migrate to AWS. By implementing a central-pipeline architecture using Apache Kafka to sync on-prem and cloud deployments, companies can accelerate migration times and reduce costs.

In this online talk we will cover:
•How to take the first step in migrating to AWS
•How to reliably sync your on premises applications using a persistent bridge to cloud
•Learn how Confluent Cloud can make this daunting task simple, reliable and performant
•See a demo of the hybrid-cloud and multi-region deployment of Apache Kafka

With 3.6 million paid print and digital subscriptions, how did The New York Times remain a leader in an evolving industry that once relied on print? It fundamentally changed its infrastructure at the core to keep up with the new expectations of the digital age and its consumers. Now every piece of content ever published by The New York Times throughout the past 166 years and counting is stored in Apache Kafka®.

Join The New York Times' Director of Engineering Boerge Svingen to learn how the innovative news giant of America transformed the way it sources content while still maintaining searchability, accuracy and accessibility through a variety of applications and services—all through the power of a real-time streaming platform.

In this talk, Boerge will:
-Provide an overview of what the publishing infrastructure used to look like
-Deep dive into the log-based architecture of The New York Times’ Publishing Pipeline
-Explain the schema, monolog and skinny log used for storing articles
-Share challenges and lessons learned
-Answer live questions submitted by the audience

In this session, Nick Dearden covers the planning and operation of your KSQL deployment, including under-the-hood architectural details. You will learn about the various deployment models, how to track and monitor your KSQL applications, how to scale in and out and how to think about capacity planning.

This is part 3 out of 3 in the Empowering Streams through KSQL series.

Analytic pipelines running purely on batch processing systems can suffer from hours of data lag, resulting in accuracy issues with analysis and overall decision-making. Join us for a demo to learn how easy it is to integrate your Apache Kafka® streams in Apache Druid (incubating) to provide real-time insights into the data.

-The benefits of combining a real-time streaming platform with a comprehensive analytics stack
-Building an analytics pipeline by integrating Confluent Platform and Imply
-How KSQL, streaming SQL for Kafka, can easily transform and filter streams of data in real time
-Querying and visualizing streaming data in Imply
-Practical ways to implement Confluent Platform and Imply to address common use cases such as analyzing network flows, collecting and monitoring IoT data and visualizing clickstream data

Confluent Platform, developed by the creators of Kafka, enables the ingest and processing of massive amounts of real-time event data. Imply, the complete analytics stack built on Druid, can ingest, store, query and visualize streaming data from Confluent Platform, enabling end-to-end real-time analytics. Together, Confluent and Imply can provide low latency data delivery, data transform, and data querying capabilities to power a range of use cases.

Join us as we build a complete streaming application with KSQL. There will be plenty of hands-on action, plus a description of our thought process and design choices along the way. Look out for advice on best practices and handy tips and tricks as we go.

This is part 2 out of 3 in the Empowering Streams through KSQL series.

Can your organization react to customer events as they occur?
Can your organization detect anomalies before they cause problems?
Can your organization process streaming data in real time?

Real time and event-driven architectures are emerging as key components in developing streaming applications. Nearly half of organizations consider it essential to process event data within seconds of its occurrence. Yet less than one third are satisfied with their ability to do so today. In this webinar featuring Dave Menninger of Ventana Research, learn from the firm’s benchmark research about what streaming data is and why it is important. Joanna Schloss also joins to discuss how event-streaming platforms deliver real time actionability on data as it arrives into the business. Join us to hear how other organizations are managing streaming data and how you can adopt and deploy real time processing capabilities.

In this webinar you will:
-Get valuable market research data about how other organizations are managing streaming data
-Learn how real time processing is a key component of a digital transformation strategy
-Hear real world use cases of streaming data in action
-Review architectural approaches for adding real time, streaming data capabilities to your applications

Capital One supports interactions with real-time streaming transactional data using Apache Kafka®. Kafka helps deliver information to internal operation teams and bank tellers to assist with assessing risk and protect customers in a myriad of ways.

Inside the bank, Kafka allows Capital One to build a real-time system that takes advantage of modern data and cloud technologies without exposing customers to unnecessary data breaches, or violating privacy regulations. These examples demonstrate how a streaming platform enables Capital One to act on their visions faster and in a more scalable way through the Kafka solution, helping establish Capital One as an innovator in the banking space.

Join us for this online talk on lessons learned, best practices and technical patterns of Capital One’s deployment of Apache Kafka.

-Find out how Kafka delivers on a 5-second service-level agreement (SLA) for inside branch tellers.
-Learn how to combine and host data in-memory and prevent personally identifiable information (PII) violations of in-flight transactions.
-Understand how Capital One manages Kafka Docker containers using Kubernetes.

This session covers the patterns and techniques of using KSQL. Tim Berglund discusses the various building blocks that you can use in your own applications, starting with the language syntax itself and covering how and when to use its powerful capabilities like a pro.

This is part 1 out of 3 in the Empowering Streams through KSQL series.

Confluent, founded by the creators of open source Apache Kafka®, provides the leading streaming platform that enables enterprises to maximize the value of data. Confluent Platform empowers leaders in industries such as retail, logistics, manufacturing, financial services, technology and media, to move data from isolated systems into a real-time data pipeline where they can act on it immediately.

Backed by Benchmark, Index Ventures and Sequoia, Confluent is based in Palo Alto, California. To learn more, please visit www.confluent.io.